A hybrid algorithm based on PSO and SA and its application for two-dimensional non-guillotine cutting stock problem

Abstract

In this paper we present a hybrid algorithm based on Particle Swarm Optimization (PSO) and Simulated Annealing (SA) approaches and apply it to two-dimensional non-guillotine cutting stock problem. The probability of trapping at the local optimum during the searching process can be reduced using the hybrid algorithm. Meanwhile, we propose a converting approach which is similar to the Bottom Left (BL) algorithm to map the cutting pattern to the actual layout. Finally, we implement the proposed algorithm on several test problems. The simulated results show that the performance of the hybrid algorithm is better than that of the standard PSO. © Springer-Verlag Berlin Heidelberg 2004.